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Give AI assistants local knowledge retrieval, persistent memory, and multi-agent collaboration.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "OpenLMlib" yet — see the docs or source repo.
Use OpenLMlib to connect my local papers and notes, semantically search for 'RAG evaluation methods', summarize the key points, and save this research session as persistent memory for later use.
Returns summarized findings with source references and stores the session as persistent local memory.
With OpenLMlib, run a full-text search across my project documents for 'API rate limit' and 'fallback strategy', then list matching files, passages, and brief conclusions.
Outputs matched documents, relevant excerpts, and a short synthesis based on the results.
Using OpenLMlib, create a multi-agent workflow where one agent searches local sources, one verifies facts, and another drafts the final report on 'open-source vector database selection recommendations'.
Generates a coordinated research output with verified conclusions and a final draft report.
Give AI assistants persistent memory with tagged retrieval, links, and source references.
Search the web locally and generate grounded answers with an Ollama model.
Provide persistent shared memory, entity extraction, and hybrid search for AI tools.
Turn local notes into a private searchable knowledge base for AI assistants.
Give LLMs persistent local memory and semantic recall across sessions.
Give AI assistants persistent memory, semantic search, and team collaboration.